A Machine Learning (ML) Approach for Early Identification of Prodromal Parkinson’s Disease (PD) (P2-5.011)

Aim is to analyze available data of voice, Tappy keystroke, spiral drawings, and gait data involving PD patients and controls available in public databases using machine learning models and identify early PD characteristics.

Authors

Publication Details

Journal
Neurology
Published
2025-04-07
DOI
https://doi.org/10.1212/wnl.0000000000210344
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
0.00
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article

A Machine Learning (ML) Approach for Early Identification of Prodromal Parkinson’s Disease (PD) (P2-5.011)

Anisha Vaish
2 links
Neurology
Parkinson's Disease Mechanisms and Treatments
article

A Machine Learning (ML) Approach for Early Identification of Prodromal Parkinson’s Disease (PD) (P2-5.011)

Anisha Vaish
article en

Abstract

Aim is to analyze available data of voice, Tappy keystroke, spiral drawings, and gait data involving PD patients and controls available in public databases using machine learning models and identify early PD characteristics.

NeurologyVol. 104(7_Supplement_1)
Openalex Percentile: Top 88%
Parkinson's Disease Mechanisms and Treatments
DOISourceOpenAlex
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A Machine Learning (ML) Approach for Early Identification of Prodromal Parkinson’s Disease (PD) (P2-5.011) — Anisha Vaish · Neurology (2025) | TGRS Research Map | TGRS